633 results about "Web technology" patented technology

The present invention discloses an artificial intelligence-based adaptive big data storage and retrieval optimization system and method designed to intelligently manage and optimize large-scale distributed data environments. The system integrates data acquisition, distributed storage, metadata processing, adaptive learning, and retrieval optimization units configured to work collaboratively for continuous self-optimization. The invention employs deep reinforcement learning and predictive neural network techniques to dynamically analyze system telemetry, workload behavior, and data access patterns in real time, enabling proactive adjustment of data placement, caching, replication, and compression parameters across distributed nodes. The metadata processing framework utilizes graph-based dependency modeling to maintain semantic and contextual relationships among datasets, facilitating intelligent and context-aware data retrieval. The retrieval optimization unit interprets user queries semantically and computes the optimal retrieval route using latency prediction models and dynamic routing techniques.

The invention discloses a QoS guarantee method and system for a communication network, and relates to the technical field of communication networks, and the method comprises the steps: collecting and preprocessing network state data, and forming a standardized data set; dynamically classifying service types based on an improved random forest algorithm, and predicting a future QoS demand trend of each priority service in combination with an LSTM neural network; establishing a mapping model of QoS demands and resource parameters, converting predicted demands into allocable resource indexes, monitoring the resource utilization rate in real time, and setting an elastic reservation mechanism and conflict early warning; when early warning is triggered, selecting an optimal transmission link by adopting a multi-path collaborative algorithm, and implementing differentiated resource allocation according to service priorities; and a closed-loop feedback mechanism is triggered to dynamically adjust resource allocation by monitoring the deviation between the actual QoS and a predicted value in real time. The method has the advantages that through multi-dimensional perception, LSTM prediction, dynamic resource management and multi-path scheduling, QoS requirements of services with different priorities are accurately matched, and dynamic changes of the network are efficiently coped with.

The invention provides an Internet of Vehicles vulnerability management method, system, device and medium based on a block chain, and relates to the technical field of vehicle networks, the method can comprehensively identify potential safety risks of vehicles through a dynamic and static combined vulnerability detection mechanism, and generates a structured vulnerability report; hash abstract chaining evidence storage is performed on key data of reports and subsequent repair links by using a block chain, so that the whole process of vulnerability discovery, analysis and repair is ensured not to be tampered and traceable, and the authenticity and credibility of data are improved; the integrity of the report is verified at the cloud end, and an AI analysis engine is combined to associate a CVE database and threat intelligence, so that intelligent generation and decision support of a repair scheme are realized; the hash abstract on the chain of the OTA patch is verified at the vehicle end, so that the credibility of the patch source and the integrity of the content are guaranteed; and finally, through feedback of an installation result and secondary uplink archiving, complete closed-loop management from vulnerability discovery to repair verification is formed.

The invention relates to the technical field of communication networks, in particular to a dynamic resource allocation method and system for an industrial 5G network. The method comprises the following steps: acquiring industrial terminal data; identifying network congestion nodes based on industrial terminal data; detecting a link congestion fault according to the network congestion node, and determining a bandwidth utilization rate; allocating spectrum resources based on the bandwidth utilization rate; performing frequency spectrum slicing on the frequency spectrum resources, and determining a flow load amount; adjusting load balance according to the traffic load, and generating a load resource report; dynamically adjusting time slot allocation by using a load resource report, and determining a task priority; task scheduling simulation is executed according to the task priority, and if congestion occurs, a congestion snapshot is stored; reducing scheduling conflicts according to the congestion snapshots, releasing bandwidth resources, and determining available network slice capacity; power resources are dynamically adjusted based on available network slice capacity. The bandwidth utilization rate and the task scheduling efficiency of the industrial 5G network are improved based on the communication network technology.

The invention discloses a complex environment information acquisition method based on a sensor network, and relates to the technical field of sensor networks, and the method comprises the steps: building a complex environment portrait and a service level, and generating a scene configuration comprising an information freshness budget, a risk heat map and an alarm threshold; based on scene configuration, configuring mesh wireless networking, time synchronization parameters and candidate relays, and constructing observation configuration and quality rules; and generating a data stream and a real-time queue state according to a self-adaptive sampling strategy and an event mark, calculating an emergency degree and distributing a forwarding probability according to an information freshness budget by combining a candidate relay and a risk heat map, outputting uploaded data and a quality record, completing convergence and grading alarm according to an alarm threshold, and generating a disposal feedback and audit index. The state set, the uncertainty set, the link idle degree and the energy sufficiency are linked under the constraint of the information freshness budget, so that hot spot encryption, low-risk sparseness, reduction of energy consumption and conflict rate and standard observation time efficiency are realized.

The invention relates to the technical field of communication networks, in particular to a resource allocation system and method in a satellite-ground fusion network, and the system comprises a satellite-ground topology and channel evolution predictor which is used for obtaining satellite ephemeris, user GNSS positioning and moving vectors, ground base station topology and a real-time CQI / RSRP measurement report; generating future link state information; the business QoE impact and switching cost modeling device is used for calculating transient interruption time of a switching action; generating switching cost information; the continuity risk quantification engine is used for generating continuity risk information containing the link maintaining risk probability, the instantaneous impact collapse probability and the link switching risk probability; the risk evasion type resource decision-making device is used for calculating maintenance link comprehensive cost and switching link comprehensive cost; calculating a dynamic switching damping threshold value; generating risk avoidance decision information; according to the invention, the high-frequency ping-pong switching near the edge state point is effectively inhibited, and the signaling overhead caused by invalid switching is reduced.

The invention relates to the technical field of industrial communication networks, in particular to a method for quickly forwarding messages from a PCIE (Peripheral Component Interface Express) interface to a WIA (Wireless Interface Architecture) interface, which comprises the following steps of: simultaneously receiving PCIE messages and WIA-FA protocol messages through a hardware logic circuit; analyzing the message in a data link layer to obtain an analysis result comprising data load and address information; packaging the analysis result according to a pre-configuration rule to generate a data frame conforming to a target protocol; and constructing a sending descriptor for the generated data frame, and sending the data frame from a corresponding interface through a direct memory access mechanism. According to the method, parallel analysis and protocol conversion of messages are achieved through a hardware logic circuit, fast address conversion is achieved through a pre-configured address mapping table, and zero-copy data transmission is achieved through a direct memory access mechanism. According to the invention, software protocol stack processing is replaced by a hardware processing flow, so that communication delay and CPU resource consumption are effectively reduced.

The invention provides a tunnel three-dimensional geologic body modeling method and system based on in-hole camera shooting and while-drilling lithology perception, and relates to the technical field of tunnel and underground engineering and intelligent geological information processing.The method comprises the steps that firstly, a drill hole wall optical image sequence and while-drilling engineering parameters are synchronously collected and preprocessed respectively; then establishing a depth-time mapping relation to realize accurate alignment of the multi-source data in a depth domain; then fracture intelligent identification and parameter extraction are realized through an improved U-Net network, and lithology classification is completed by using an XGBoost model; feature level and decision level fusion is carried out on the fracture features and the lithologic features, and rock mass quality grades are generated; and finally, constructing an integrated geologic model fusing lithologic distribution and a three-dimensional fracture network by adopting an implicit modeling and discrete fracture network technology. According to the method, the problem of splitting of in-hole visual information and while-drilling physical information is solved, automation and precision of geological recognition are improved, and reliable geological information support is provided for tunnel construction safety and support design.

The invention relates to the technical field of computer networks, in particular to a webpage project construction and access control method, which comprises the following steps: acquiring a Web project source code file, packaging the Web project source code file, configuring a root directory to correspond to the action of a rendering page, and generating a packaged resource file; uploading the packaged resource file to a code warehouse for code hosting, triggering an assembly line execution process, and storing the packaged resource file in a workpiece generated in the assembly line execution process; receiving an access request of a user, and determining item positioning information through a unique identifier in the access request; verifying the user access authority; if the user permission state indicates that the user permission verification is passed, requesting a corresponding resource file from a workpiece, and generating rendering page information containing API basic address information; and sending the rendering page information to a browser for page rendering.

The invention discloses a cloud edge cooperative multi-channel converged communication control method and system, belongs to the technical field of wireless communication networks, and aims to improve the high efficiency, reliability and real-time performance of multi-channel converged communication in a complex scene. The method specifically comprises the following steps: constructing a hierarchical collaborative architecture of a cloud end and an edge end; the edge end collects network state parameters of various communication channels, outputs a channel quality evaluation value based on a time sequence prediction model, and performs multi-channel data transmission through an extended communication protocol when triggering channel switching; the edge end executes network parameter configuration, flow priority scheduling and running state data acquisition operation, and the cloud end generates a soft routing optimization instruction based on running state data and issues the soft routing optimization instruction to the edge end to execute and adjust network transmission performance parameters; and monitoring the container operation state and the equipment state of the edge end in real time, when a monitoring result is matched with a preset abnormal rule, generating alarm information by the edge end, returning the alarm information to the cloud end to generate a global security policy, and issuing the global security policy to the edge end to update the preset abnormal rule.

The invention provides an optimized kernel network and an implementation method thereof, and relates to the technical field of kernel networks, the kernel network comprises a fast data channel component XDP arranged on a data link layer; when the network card equipment receives a message data packet, the XDP analyzes and filters the received data packet, or encapsulates or de-encapsulates the received data packet, and modifies a field to forward the data packet; and the XDP matches and filters the received data packet with the rules in the BPF Maps, and discards the data packet when the data packet is illegal. The method comprises the steps that hardware initialization comprises the step of adding a zero copy processing flow when an NAPI polling point processing function is added; the application program configures an XDP socket; the xsk unit executes a BPF instruction, calls a network card driving unit to configure an XSK cache pool, and establishes a DMA mapping relationship between the device and the UMEM shared cache; and the network card drives zero-copy receiving and receiving of the data packet. According to the invention, the kernel network communication efficiency is improved.

The invention belongs to the technical field of communication networks, and discloses a block chain topology-consensus co-evolution method and system based on reinforcement learning, and the method comprises the steps: collecting the state information of each node in a block chain network, carrying out the standardization processing and multi-dimensional feature extraction of the state information of each node, and obtaining a block chain topology-consensus co-evolution model; mapping into node state feature vectors available for reinforcement learning, and forming node state codes; a reinforcement learning strategy space is constructed according to the node state codes, a topology evolution strategy is dynamically generated by using a strategy iteration method, and topology adaptive evolution of the block chain network is realized; a structural dynamic constraint mechanism is introduced in the reinforcement learning process, and endogenous driving of topological evolution is carried out; calculating the dynamic difference between the potential energy change between the block chain network nodes and the global structure entropy, establishing an evolution constraint function, and dynamically updating the topological evolution strategy parameters; and the elasticity and the expandability of the network structure are effectively improved.

The invention provides an electric power computing network multi-dimensional resource scheduling method, device and platform and a storage medium, and belongs to the technical field of electric power computing power networks, and the method comprises the steps: obtaining the request information of a current service terminal and the computing power resource information of a cloud side computing node; determining an end-to-end time delay constraint, a cloud edge computing power resource constraint and a cloud edge end network bandwidth constraint of the intelligent server; according to the cloud edge computing power unit price and the network bandwidth unit price, determining an objective function of computing network multi-dimensional resource scheduling optimization by taking minimization of the network bandwidth and the cloud edge computing power overhead as an optimization objective; solving the plurality of scheduling constraint models to obtain an optimal solution; and outputting a computing network multi-dimensional resource scheduling strategy according to the optimal solution. According to the method, under the condition that different computing network resource service quality requirements of multiple services are considered, by dynamically deploying multi-dimensional resources such as network bandwidth, cloud computing power and edge computing power, the low response delay requirements of key services such as environmental risks and equipment faults in power grid operation are effectively met, and meanwhile it is ensured that the computing network resource consumption economical efficiency is optimal.

The invention provides a dynamic reconstruction optimization method and system for communication information network topology, and relates to the technical field of communication networks, and the method comprises the steps: firstly obtaining node operation dynamic information, link transmission real-time information and network service demand dynamic data of a communication information network; generating a network topology elastic association body containing a plurality of association rules and logics based on the two; inputting the service demand data into a network topology elastic association body to generate a network topology dynamic demand adaptation factor; generating a network topology reconstruction path self-adaptive sequence containing a specific operation instruction and a time sequence based on the network topology dynamic demand adaptation factor and the network topology elastic correlation body; and adjusting a node connection mode and link transmission configuration in a linkage manner according to a network topology reconstruction path self-adaptive sequence, and synchronously updating an association rule to complete dynamic reconstruction optimization. According to the invention, the network stability, reliability and resource utilization rate are improved.

A packet forwarding method, apparatus, and system are provided, and belong to the field of network technologies. A destination address field of a first packet received by a first network node includes a compressed segment identifier corresponding to a first outbound interface or a next-hop node of the first network node; based on the first outbound interface being faulty or the next-hop node being faulty, the first network node determines a second segment identifier based on segment identifier planning information of the node corresponding to the compressed segment identifier, and forwards the first packet based on the second segment identifier, where the second segment identifier is a segment identifier in a segment list of the first packet or a segment identifier in the destination address field.

The invention belongs to the field of Web application technology, XML document processing technology and online editor technology, and discloses an XML semantic editing system based on an aviation knowledge graph. The system comprises a front-end application module, an XML processing engine module, a DTD rule verification module, a visual editing module, a plug-in extension module, a collaborative editing module and an aviation knowledge graph integration module. According to the method, professional and efficient editing of XML documents in the aviation field is achieved through the full-process design of front-end interaction, XML processing, DTD verification, visual editing, semantic assistance and collaborative management, and the Web technology, the XML processing technology, the DTD verification technology, the knowledge graph technology and the collaborative editing technology are integrated, so that the XML documents in the aviation field are edited in a professional and efficient mode. The problems that an existing XML editing tool is difficult to deploy, poor in compliance, low in efficiency and weak in cooperation in the aviation maintenance field are solved, and a specialized and efficient XML semantic editing scheme is provided for the aviation maintenance industry.

The invention discloses an SRv6 computing power network path optimization method and system based on multi-dimensional dynamic scoring, and belongs to the technical field of communication networks, and the method comprises the steps: building a multi-dimensional dynamic scoring system of load scoring, delay scoring and service priority scoring through collecting node loads, link congestion, geographic distances, topology hops and service types in real time; the method comprises the following steps: dynamically selecting an optimal path based on a DMPSC-T table (including a LastUpdate Time / ExpireTime timestamp mechanism); and when a better path is detected, an End.Redit instruction newly defined by SRv6 is utilized to trigger SID dynamic replacement: an Endpoint node directly replaces a target SID in a SegmentList, and a transfer node generates an ACL rule through a PBR to realize redirection. According to the invention, millisecond-level path switching can be realized, the service quality of high-priority business is effectively improved, and the global scheduling efficiency of network resources is optimized.

The invention belongs to the technical field of nuclear power station maintenance management, and particularly relates to a nuclear power maintenance decision-making system and method based on multi-Agent cooperation. The system comprises an input layer, a multi-Agent cooperation layer, a knowledge support layer, a decision processing layer, an output and interaction layer and a feedback learning layer. The input layer receives initial work order information including equipment basic information and fault description; the multi-Agent collaboration layer allocates sub-tasks to predefined six types of professional Agents according to work order information and completes information interaction; the knowledge support layer comprises a nuclear power professional knowledge base, a historical maintenance database and a rule and regulation library; the decision processing layer performs conflict detection, negotiation and decision fusion on Agent output; the output and interaction layer provides a decision result display and man-machine interaction interface; and the feedback learning layer realizes comprehensive improvement of nuclear power maintenance decision-making efficiency and safety. The method has the beneficial effects that a multi-professional Agent collaborative network technical means is adopted, and the technical effects of maintenance decision cross-professional information instant sharing and efficient collaboration are realized.

The invention discloses an AI large model-oriented financial private network optimization method and system, and relates to the technical field of communication networks. According to the method, an exclusive path strategy is generated for AI training, reasoning and sensitive data traffic by collecting AI service requirements and network states and utilizing the SID programming capability of SRv6; the load of the computing power node is monitored in real time, the computing power state is linked with network scheduling, and network-computing power collaborative optimization is realized; a hop-by-hop path authentication mechanism based on a dynamic authentication segment identifier Auth-SID is introduced, so that the security of a data transmission path is enhanced; and end-to-end visual operation and maintenance and closed-loop feedback of the service flow are realized by adopting a flow-following detection technology. According to the invention, the problems of mismatching of flow scheduling and AI service requirements, insufficient network and computing power collaboration, lack of path security guarantee and weak operation and maintenance visualization capability in the prior art are solved, deep adaptation of network resources and the AI service requirements is realized, and the computing power collaboration efficiency, the path security and the operation and maintenance intelligence level are improved.

The invention discloses a back-to-source testing method, computer equipment and a storage medium, and relates to the technical field of content distribution networks, and the back-to-source testing method realizes active pushing of configuration information through a mode of sending complete configuration information to a source station server in advance before validity testing; therefore, after the source station server receives the back-to-source request of the target edge server, the configuration information carried by the back-to-source request can be finely compared with the configuration information stored in the source station server, and the back-to-source test result is fed back to the client in real time after the comparison is completed, so that the client can know the processing condition of the back-to-source request in time, and the processing efficiency of the back-to-source request is improved. And corresponding operation can be carried out in time according to the feedback result. In the whole back-to-source test process, tedious operations such as packet capturing by using a packet capturing tool at the source station server are not needed, the CDN configuration effective test can be rapidly and accurately completed, the whole test period is shortened through the rapid and efficient test process, and therefore the efficiency and quality of back-to-source test work are greatly improved.

The invention discloses a multilayer space dynamic topology adaptive communication network construction method, and belongs to the technical field of communication networks. The method is realized through five steps of constructing a multi-layer fusion architecture of space-based, air-based and ground-based networks, instantiating network slices of power service perception, performing dynamic topology abstraction and resource pre-mapping based on virtual cell division, performing power and bandwidth collaborative allocation based on reinforcement learning, and deploying multi-domain fault diagnosis and predicting a closed loop. According to the invention, power and bandwidth collaborative allocation based on deep reinforcement learning not only can optimize the total capacity of the system, but also can realize dynamic balance of the network load. The system can automatically adjust the power and bandwidth distribution according to the real-time network state in the operation process, and the self-adaptive mechanism enables the network to efficiently cope with the demand changes of different power businesses.

The invention belongs to the technical field of wireless communication and networks, and discloses a time-frequency resource joint scheduling method and system for unmanned aerial vehicle emergency service real-time return, and the method comprises the steps: employing a graph theory, and constructing an unmanned aerial vehicle emergency communication network into a dynamic directional conflict graph; based on a dynamic directional conflict graph, through a dynamic directional double graph coloring algorithm based on a dobby machine, combined scheduling of time-frequency resources of the unmanned aerial vehicle in a time-varying topology scene is realized, and reliable return of disaster situation data in a post-disaster high-dynamic emergency scene is solved.

The invention belongs to the technical field of computer networks, and discloses a resource-constrained network equipment-oriented double-layer GRU lightweight real-time network anomaly detection method, which comprises the following steps of: constructing an anomaly detection model and training, deploying the trained model to resource-constrained network equipment, the method comprises the following steps: acquiring a system log generated when network flow generated by each application server node flows through in real time, performing data preprocessing on the acquired system log to obtain log semantic vectors, and forming a window sequence by the continuous log semantic vectors to obtain an abnormal probability value; and comparing the abnormal probability value with a set threshold value, and directly outputting an output detection result at an equipment end. According to the method, complexity of entity information is eliminated, time dependence in a time sequence is enhanced, simplification is carried out, a high anomaly detection recall rate is achieved under the condition that low calculation overhead is kept, the risk of missing detection is reduced, and cascade faults caused by the fact that anomalies are not found in time are avoided.

The invention relates to the technical field of communication networks, in particular to an intention-driven satellite-ground convergence network on-demand arrangement system and method, and the method comprises an intention input layer which is used for receiving a multi-mode intention of a user; the intention analysis layer is used for analyzing the intention of the user to generate a recognizable network strategy; the arrangement control layer comprises a design state and an operation state; wherein the design state is used for dynamically generating a resource arrangement strategy based on an identifiable network strategy, and verifying the feasibility of the resource arrangement strategy in the digital twin network; the running state is used for generating an executable scheme based on the verified resource arrangement strategy; and the infrastructure layer comprises a satellite-ground unified atomic power abstraction module which is used for abstracting heterogeneous resources into standardized atomic power and executing an executable scheme. The scheme aims to provide a brand-new intention-driven satellite-ground fusion network arrangement architecture with dynamic generation, thorough decoupling and active prediction capabilities, so that the technical problem that complexity and dynamics of a 6G network cannot be handled at present is solved.

The invention discloses an on-chip network router implementation method based on a classification conflict-free bypass, and relates to the technical field of on-chip networks. Comprising the following steps: step 1, receiving a flit of a network on chip and extracting flit information; 2, performing classification bypass condition verification according to the extracted microchip information and the load condition, and outputting a path selection signal; step 3, processing a conflict-free microchip of which the bypass enable signal is equal to 1; 4, processing the microchip of which the bypass enable signal is equal to 0; according to the method, differentiated bypass admission rules are formulated by identifying the types of the data packets, the judgment strategy is dynamically adjusted in combination with the real-time network load, meanwhile, bypass state management is simplified, and efficient forwarding and power consumption optimization of conflict-free microchips are achieved.

The invention discloses an asynchronous task message passing method, device and equipment based on an MCP protocol and a storage medium, is applied to a calling end registered as an MCP endpoint, and relates to the technical field of computer networks, and the method comprises the following steps: establishing a full duplex communication session with an execution end based on instance information issued by a service registration center, establishing task semantic information based on the initial task request by using an MCP protocol layer; a target task request is sent to the execution end through the session, and the execution end executes a task by using the Nacos service according to the target task request to generate an event flow. And when the network connection is abnormal, the calling end locates the position of the event successfully received last time based on the global unique event identifier of the event stream, generates a reconnection request and issues the reconnection request to the execution end, and the execution end returns the event stream in sequence according to the reconnection request. And the calling end sends the confirmation instruction to the execution end, the execution end generates the event confirmation sequence number and returns the event confirmation sequence number, and the calling end judges that task message transmission is completed after receiving the sequence number, so that the task message transmission efficiency is improved.

The invention provides an image tile service elastic concurrency control method and system under bandwidth constraint, and relates to the technical field of communication networks, and the method comprises the steps: inputting the collected actual bandwidth data of an image tile service into a preset time sequence prediction model, and outputting a future bandwidth use prediction value; determining a bandwidth utilization rate and a bandwidth early warning level in combination with a preset fixed exit bandwidth threshold value; when an access request is received and the bandwidth early warning level exceeds a preset early warning level, if the target image tile does not belong to the high-frequency tile set, returning the target image tile data with the original quality to the client; and otherwise, adjusting the image coding parameter of the target image tile, generating temporary tile data after quality reduction and compression, and returning the temporary tile data to the client. By implementing the method, the image browsing quality of the user can be maximized in the bandwidth unsaturated state while the high concurrency connectivity of the service is guaranteed.

The invention belongs to the technical field of intelligent humanoid robots, and discloses a remote operation data acquisition and data closed-loop system for an intelligent humanoid robot, which builds an instruction, action and acquisition ternary time sequence synchronization mechanism through a time sequence coordination module, realizes dynamic coordination of the three parts by using a time sensitive network technology, effectively reduces time sequence deviation, and improves the system performance. Meanwhile, a space-time alignment algorithm of the data processing module is combined, so that the consistency of the multi-modal data in time and space dimensions is guaranteed; acquired data can accurately fit human operation logic and a robot action state, the optimization efficiency of a data closed loop is improved, and the requirements of high-precision operation scenes such as complex assembly and flexible material processing are successfully met; a quantitative association system of data quality and control effects is established by means of the evaluation module, invalid data such as sensor faults and action fuzziness can be screened in real time, and occupation of redundant storage and computing resources is reduced.

The invention discloses a vehicle-mounted dynamic key management and verification method and device, equipment and a medium, and relates to the technical field of computer networks. In response to an encryption request for target firmware in a target vehicle, acquiring firmware information of the target firmware issued by the cloud; the firmware information comprises an identification code of a target vehicle and a firmware version number of the target firmware; performing slicing processing on the target firmware to obtain at least one firmware slice in the target firmware; generating a firmware key tree corresponding to the target firmware based on the firmware information and the original entropy; the firmware key tree comprises a root key of the target firmware and a slice key of each firmware slice. By adopting the technical scheme, the key can be dynamically managed based on firmware information such as the firmware version number, the binding of the key with the vehicle-mounted equipment and the firmware is realized, the risk that the existing static key is easy to leak is solved, and the safety of the vehicle function is improved.

The invention discloses a body-equipped robot control system and method based on multi-modal perception and deep learning, and the system comprises a multi-modal perception module which is used for obtaining and fusing visual information, tactile information and proprioceptive information, and generating a unified state representation; the deep reinforcement learning control module adopts a reinforcement learning algorithm based on an actor-commentator framework and is used for representing an output control strategy according to the unified state, and the reinforcement learning algorithm adopts an experience playback mechanism and a target network technology to realize stable learning; the hierarchical motion planning module is connected with the deep reinforcement learning control module and is used for decomposing a complex task corresponding to the control strategy into high-level strategy planning and bottom-level motion execution; the self-adaptive impedance control module is connected with the hierarchical motion planning module and is used for dynamically adjusting impedance parameters of the robot according to interaction information of the robot and the environment; and the safety guarantee module is used for applying constraint optimization to the control strategy or the motion execution so as to ensure the operation safety of the robot.